Category Archives: Spend Analysis

Spend Analysis Solution Selection: What to Look for in Software and Services

As the author penned in Spend Visibility: An Implementation Guide,

“Almost any attempt by an organization to analyze spending patterns is likely to be fruitful, especially if there hasn’t been a serious prior attempt. It is easy to find thousands of breathless testimonials about a particular product or method — independent of the quality of the product or method — because almost any product or method will find savings if a spend visibility initiative has never been launched before. In the land of the blind, the one-eyed man is king“.

This simple fact has confused end-user organizations and analysts for many years. In fact, it has convinced most spend visibility vendors (and most analysts) that spend visibility is a fundamentally simple process of mapping Accounts Payable spend, and then drilling for dollars.

But Nothing Could Be Further From The Truth!

What is not so obvious is that this initial burst of savings is short-lived; and that many of the “quick saves” that result are unsustainable.

Especially if an organization does not select the right solution in the beginning that will allow it to define, and implement, a strategy that will allow it to identify continued savings year-over-year after the initial burst of savings are captured.

However, there’s no reason for an organization not to select the right software or services, because, it’s easy to select the right solution once you are informed. If you don’t know where to start, the next Next Level Purchasing Association (NLPA) members only webinar on July 28, 2015 @ 8:30 am PDT, 11:30 am EDT, and 16:30 pm BST, will provide you with a starting point as you evaluate software and services providers.

Specifically, this webinar will focus on helping an organization identify:

  1. key features of a spend analysis platform,
  2. critical requirements for successful services, and
  3. what to look for in a full-service solution

so that the organization may achieve spend analysis success. In particular, the kind of success that will generate a year-over-year average savings of 10%+.

Space is limited, and only NLPA members will have the opportunity to attend this webinar hosted by the doctor of Sourcing Innovation, but Basic Membership is Free, so there’s no reason to miss out. Sign up today, and very shortly you’ll receive the notice of the upcoming webinar that will allow you to register for this very informative webinar.

Real World Analytics – It All Depends on the Domain

Another book that was published late last year, and that has been sitting on the doctor‘s stack for review since about then, is Real-World Analytics by Michael Koukounas. the doctor has to admit that he was a bit hesitant to review this (and then lost it in the stack) because, as he just finished explaining to yet another individual before penning this post, Spend Analysis is not the same as Data Analysis, and that’s why so many companies without any understanding of the unique requirements of spend analysis for Sourcing and Procurement (who hire hard-core computer scientists who write trite like Spend Analysis: The Window into Strategic Sourcing (which is about the only book the doctor has ever reviewed that he has completely shredded) that, as it’s title suggests, gives you a cloudy window view that doesn’t give you the full picture (and often causes you to make the wrong assumptions about what is going on in the house).

But the doctor will have to admit that if you take this book as it is — a guide for building the foundation to do analytics (and not a guide for how to do them, which requires a completely different guidebook), it does a decent job. And the author — who is obviously an expert in data analytics in the Finance and Banking industry where a lot of effort goes into loan return models, credit risk prediction, and currency fluctuation models — really knows the core foundations for performing analytics quite well and does a great job discussing them.

As the author describes in various chapters, there can be no successful analytics, data nor spend, without:

  • Good Data Access
    and a Data Management Team
  • Talent
    as analytics cannot be automated
  • Operational Knowledge
    and, in particular, operational knowledge as it relates to the domain
  • Appropriate Trade-Offs Between Efficiency and Creativity
    and fine-tuning to the audience
  • an Analytics Continuity Plan
    in case something happens to top talent
  • the right teams …
    data management, analytics development, and analytics maintenance
  • … and the right team sizes
    since core development will usually only require a small team (because once the up front models are developed / implemented for the organization, new needs won’t be popping up every day), data management will require a team proportional to the number of data sources and their complexity, and maintenance will often require a larger team than you think as new data becomes available, new insights are required, and new reports are requested.

Moreover, at a high-level, the five-step game plan is correct:

  1. Define the Problem (and the end goal)
  2. Identify Touch-Points (where and when the analytics should be run)
  3. Understand the Touch Points (and the restrictions and requirements they place on the analytics)
  4. Select the Right Data (since garbage in means garbage out)
  5. Run the Analytics (and validate the results)

But when you start to descend from the 30,000 foot view, the details are vastly different in the spend analysis domain (and the author even implies this when he says that the analytic needs for engineers are vastly different than the analytic needs for financiers). But Real-World Analytics is a great guide to getting the precursor foundations right.

Maverick Spend is Good. Wait, What?

For years and years and years the doctor, the maverick, and every other thought leader in Procurement have collectively been telling you that maverick spend is bad. It erodes negotiated savings, builds mistrust in the supply base, and underlies your Procurement processes. It encourages rogue behaviour and increases the organization’s exposure to risk and liability. Good Procurement is not accomplished by loner hot-shots, but an integrated, dedicated team that manages the supply chain end-to-end and makes sure the entire chain is strong, not just one link.

But, sometimes, if approached in the proper manner, Maverick spend can be good. Maverick spend can help you identify weak processes, better products and services, preferred suppliers, and even poor definitions of on-contract and off-contract spend. Even though it’s still bad if the buyer is buying off-contract, paying more than needed, risking good supplier relationships, and potentially exposing the organization to compliance and liability issues, maverick spend still presents an opportunity to improve Procurement processes, procured products, and even personnel.

How? Check out the new Spend Matters Pro Piece in the maverick‘s 50 Shades of Pay series that was co-authored by the doctor on “Maverick Spend Analysis: How to Re-Plumb Your Spend and Savings Flow” and find out how you can knock your spend analysis success up a notch, even if you don’t have a spice weasel.

The Boxing Day Blogger’s Lament

Sorrow is my own yard
where the new grass
flames as it has flamed
often before, but not
with the cold fire
that closes round me this year.

For five straight years
On this day we spend rapped.
The web page is white today
no insights from grey beards.
Insights on spending
once filled many pages
put colour in our cheeks.

Yellow and some red,
but the grief in my heart
is stronger than they,
for though they were my joy
formerly, today they are absent
and we do miss old grey beard.

Today a bird told me
that in the meadows,
at the edge of the heavy woods
in the distance, he saw
a glimpse of grey beard.
I feel that I would like
to know that
the old grey beard will return
and bring us a spend rap again.

Procurement Trend #06. Data-Based Predictive Analytics

Three annoying anti-trends remain. We’re so close to the end that we can almost taste the bitter-sweet victory, but the sour taste in our mouths still remains as we must continue to provide those fashionably-challenged futurists with counter-examples to the trends of their fore-fathers that no one who didn’t lock themselves in a windowless padded room would try to pass off as a trend of tomorrow. We want to shame them for their stupidity, but we will leave their hard-earned humiliation for LOLCat, who is obviously quite fed up at having to spend yet another life listening to their ludicrousness, but still finding the time to point out how LOLCats have been sustainable at least since the first corrugated cardboard box was created.

So why do these pit-dwelling prophets from Hawalius keep pushing us trends from the rubbish pile? Besides the fact that some of them obviously spent the best part of last decade in a rancid cave, probably because they look around, see the laggard organizations still struggling with last decade’s technology, and assume they can still sell last decade’s leftover snake oil in today’s marketplace. Thus, if most organizations are struggling with proper historical spend analysis, data-based predictive analytics is obviously a future trend, and

  • good decisions require good data

    and so few organizations have good data

  • inventory forecasting is getting harder and harder

    as sudden changes in unemployment rate, interest rates, and brand sentiment as well as unexpected supply chain delays or competitive product introductions can all have a large impact on demand

  • market prices are getting even harder to predict in volatile markets

    and profitability often depends on slim margins

Which would be great reasoning if leading organizations hadn’t figured this out over a decade ago and moved on to doing something about it a while ago!

So what does this mean to you?

Clean and Enrich Your (Master) Data

Dirty data dictates dastardly decisions. And those never end well. But don’t go crazy trying to do it. 100% clean data is a pipe dream, and, as with most situations, the 80/20, or, to be more precise, the 90/10 rule applies. Clean and enrich as required to confidently map 90%+ of spend, including 90%+ of the spend for the top 90%+ of suppliers and the top 90%+ of products. Stop when the effort exceeds the return. With a good mapping tool, the mapping can be done for even the largest Fortune 500 by hand in a week. Depending on how good the data is, the analyst might even get to 95% or even 98%. Then, identify any glaring weaknesses (such as supplier financial or risk data, market data, or cost breakdowns relative to a Bill of Material) that are important from a spend analysis or should cost modelling viewpoint, and get that data.

Put Protocols and Safeguards in Place to Keep your (Master) Data that Way

It’s going to take time, money, and manpower to map, clean, and enrich the data. This will be time, money, and manpower wasted if protocols aren’t put in place to make sure not just anyone can update master data, or at least not without review and verification. Put workflows and approvals in place to minimize the chances of bad data getting into the system or data getting out of whack too quickly.

Automatically Augment Your (Master) Data with Market Data

Good historical data is good. But current market data is better. With past and current data you can not only know current conditions, but with current market data, updated regularly, you can compute trends.

Use All the Data to Predict Trends and Make Sourcing Decisions

Use the computed trends to predict likely future conditions based upon the trends and current market movements. Based on this data, you can judge whether or not it is a good time to source a category and lock in long-term pricing.